ClawHub

Garmin

Data & APIs

Integrate with Garmin Connect to fetch and analyze deep fitness metrics including sleep, body battery, resting heart rate, stress, and training status. Use this skill for enhanced training insights, recovery-aware nudges, and daily health summaries.

Install

openclaw skills install garmin-connect-thebyteio

Garmin Connect Integration Skill

Deep fitness metrics from Garmin Connect for enhanced training insights and recovery-aware nudges.

Features

  • Training Status: Recovery time, training load, VO2 max
  • Sleep Analysis: Duration, quality, sleep stages
  • Body Battery: Energy levels throughout day
  • Daily Readiness: Is Brian recovered enough to train hard?
  • Heart Rate: Resting HR trends, stress levels
  • Activity Details: More detailed metrics than Strava

Why Garmin + Strava?

Strava: Social, activities, segments, ride tracking
Garmin: Physiological metrics, recovery, sleep, training load

Combined = Smart nudges that respect recovery status!

Setup

1. Install Dependencies

pip3 install garminconnect --break-system-packages
# Or using a virtual environment (recommended):
# python3 -m venv ./venv
# source ./venv/bin/activate
# pip install garminconnect

2. Store Credentials in 1Password

Create a new "Login" item in your 1Password vault (e.g., "Personal") with the following details:

  • Title: Garmin Connect (or a custom name you prefer)
  • Username: Your Garmin Connect email address
  • Password: Your Garmin Connect password

If you use a custom title or a different vault, set the GARMIN_1P_ITEM_NAME and GARMIN_1P_VAULT environment variables before running the scripts. Example:

export GARMIN_1P_ITEM_NAME="My Garmin Login"
export GARMIN_1P_VAULT="MyFamilyVault"

Ensure your OP_SERVICE_ACCOUNT_TOKEN is set up for 1Password CLI authentication:

export OP_SERVICE_ACCOUNT_TOKEN=$(cat ~/.config/op/service-account-token)

3. Test Connection

./scripts/garmin-login.sh

Usage

Get Today's Stats

./scripts/get-stats.sh

Returns:

  • Body battery (current/forecast)
  • Sleep last night
  • Training status
  • Recovery time remaining
  • Resting heart rate

Get Sleep Data

./scripts/get-sleep.sh [days_back]

Returns sleep duration, quality, stages for last N days.

Check Recovery Status

./scripts/check-recovery.sh

Returns whether Brian is recovered enough for hard training.

Integration with Strava Nudges

Enhanced decision logic:

Before nudging for a hard workout:

  1. Check Garmin recovery time
  2. Check body battery level
  3. Check sleep quality last night
  4. Adjust intensity recommendation

Example:

  • Strava says: "Thursday tempo ride"
  • Garmin says: "Recovery time: 24h, body battery: 45%"
  • Nudge becomes: "Thursday ride scheduled, but recovery still needed. Easy Zone 2 instead of tempo today?"

Data Structure

Stats Object

{
  "body_battery": {
    "current": 75,
    "charged": true,
    "forecast": 85
  },
  "sleep": {
    "duration_hours": 7.2,
    "quality": "good",
    "deep_sleep_hours": 1.8,
    "rem_hours": 1.5
  },
  "training_status": {
    "status": "productive",
    "vo2_max": 52,
    "recovery_time_hours": 12
  },
  "heart_rate": {
    "resting": 48,
    "current": 62,
    "stress_level": 25
  }
}

Smart Nudge Enhancement Examples

Scenario 1: Poor Sleep + Hard Workout Day

Without Garmin: "Thursday tempo ride time!"
With Garmin: "You only got 5 hours sleep last night. Maybe take today easy? Light Zone 2 or rest."

Scenario 2: Recovered + Good Conditions

Without Garmin: "Tuesday ride day"
With Garmin: "Fully recovered (body battery 85%, 8h sleep) + perfect weather. Great day for that tempo ride! 🚴"

Scenario 3: High Stress Day

Without Garmin: "Evening gym time!"
With Garmin: "Stress level high today (68). Maybe skip gym and prioritize recovery?"

Morning Briefing Enhancement

Current:

🚴 Fitness Update:
Last ride: 2 days ago
This week: 3 rides, 87km

With Garmin:

🚴 Fitness Update:
**Sleep:** 7.5h (good quality, 2h deep)
**Recovery:** ✅ Fully recovered
**Body Battery:** 82% (charged overnight)
**Resting HR:** 48 bpm (normal)

Last ride: 2 days ago
This week: 3 rides, 87km
**Training Status:** Productive (VO2 max: 52)

Configuration

Edit config.json (create if it doesn't exist):

{
  "recovery_thresholds": {
    "body_battery_low": 40,
    "body_battery_good": 70,
    "min_sleep_hours": 6.5,
    "max_recovery_time_hours": 12
  },
  "nudge_modifications": {
    "respect_recovery": true,
    "downgrade_intensity_if_tired": true,
    "skip_gym_if_high_stress": true
  }
}

Note: This config.json should be created in the skill's root directory (/root/clawd/skills/garmin/).

API Reference

Using garminconnect Python library:

  • get_stats() - Daily stats summary
  • get_sleep_data() - Sleep metrics
  • get_body_battery() - Energy levels
  • get_training_status() - Training load, recovery
  • get_heart_rates() - HR data

Rate limits: No official limit, but be reasonable (cache data, don't spam).

Dependencies

  • Python 3.7+
  • garminconnect library
  • 1Password CLI (op)
  • jq for JSON parsing (if needed by other scripts)

Privacy

  • ✅ Credentials stored in 1Password
  • ✅ Session tokens cached temporarily in /tmp/garmin-session/
  • ✅ Data queried on-demand, not stored long-term by the skill (though the system might cache in /root/clawd/data/fitness/garmin/ as per TOOLS.md)
  • ✅ No external sharing
  • ✅ Read-only access to Garmin

Future Enhancements

  • Correlate sleep quality → work productivity
  • Predict when Brian will be recovered
  • Compare son's Garmin data (if he has one)
  • Long-term trends (fitness improving?)
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